Round 1 Winners!
Proof of Usefulness Report

Rhypt

Analysis completed on 3/19/2026

+38
Proof of Usefulness Score
You're In Business

Rhypt presents a strong technical premise in data protection and algorithmic obfuscation led by PhD founders, addressing a highly relevant market need in AI privacy. However, the submission suffers from severely exaggerated and unsubstantiated traction claims (e.g., 'most people have used my product', audience reach 'everyone') and poor response quality. The score reflects high technical innovation but penalizes heavily for lack of verifiable real-world adoption.

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Score Breakdown

Real World Utility+17.50
Audience Reach Impact+1.00
Technical Innovation+12.00
Evidence Of Traction+1.25
Market Timing Relevance+8.50
Functional Completeness+0.25
Subtotal+40.5
Usefulness Multiplierx0.95
Final Score+38

Project Details

Project URL
Description
RHYPT strives to equip businesses and individuals with the power to protect both information and algorithms through every step of the data life cycle: in storage, during transport, and while processing. Using patented technology, RHYPT expands the potential for both data owners and algorithm builders to take machine learning and artificial intelligence even further. Our data protection methods allow companies with sensitive data to access powerful insights while keeping the information safe. The algorithm obfuscation and encryption techniques used give companies the ability to deploy their valuable intellectual property to a broader customer base without worrying about reverse engineering. This technology addresses the problem of protecting data in use without adding an undue computational burden. RHYPT is co-founded and led by Francois Malassenet, PhD, and Glenn Sidle, PhD.

Algorithm Insights

Market Position
Growing utility with room for optimization
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline